U.S. patent number 9,563,473 [Application Number 14/822,406] was granted by the patent office on 2017-02-07 for concurrent workload deployment to synchronize activity in a design palette.
This patent grant is currently assigned to INTERNATIONAL BUSINESS MACHINES CORPORATION. The grantee listed for this patent is International Business Machines Corporation. Invention is credited to Rahul Ghosh, Hugh E. Hockett, Aaron J. Quirk, Lin Sun.
United States Patent |
9,563,473 |
Ghosh , et al. |
February 7, 2017 |
Concurrent workload deployment to synchronize activity in a design
palette
Abstract
A system and method for iteratively deploying a workload pattern
are provided. The system and method determines a current set of
requirements for at least one piece of the workload pattern that is
initiated in a designer and generates a stability metric for at
least one of the current set of requirements. The system and method
further compares the stability metric to an acceptance threshold
and calculates an estimated time to deploy the at least one piece
of the workload pattern based on the comparing of the stability
metric to the acceptance threshold.
Inventors: |
Ghosh; Rahul (Morrisville,
NC), Hockett; Hugh E. (Raleigh, NC), Quirk; Aaron J.
(Cary, NC), Sun; Lin (Morrisville, NC) |
Applicant: |
Name |
City |
State |
Country |
Type |
International Business Machines Corporation |
Armonk |
NY |
US |
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Assignee: |
INTERNATIONAL BUSINESS MACHINES
CORPORATION (Armonk, NY)
|
Family
ID: |
56094424 |
Appl.
No.: |
14/822,406 |
Filed: |
August 10, 2015 |
Prior Publication Data
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Document
Identifier |
Publication Date |
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US 20160162339 A1 |
Jun 9, 2016 |
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Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
Issue Date |
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14560615 |
Dec 4, 2014 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F
9/4887 (20130101); G06F 9/4881 (20130101); G06F
9/5083 (20130101); G06F 9/5072 (20130101); G06F
2201/865 (20130101); G06F 11/3003 (20130101) |
Current International
Class: |
G06F
9/48 (20060101); G06F 9/50 (20060101) |
References Cited
[Referenced By]
U.S. Patent Documents
Other References
List of IBM Patents or Patent Applications Treated as Related;
(Appendix P), Filed Aug. 10; 2 pages. cited by applicant .
Rahul Ghosh, et al., "Concurrent Workload Deployment to Synchronize
Activity in a Design Palette", U.S. Appl. No. 14/560,615, filed
Dec. 4, 2014. cited by applicant.
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Primary Examiner: Kawsar; Abdullah Al
Assistant Examiner: Chu Joy-Davila; Jorge A
Attorney, Agent or Firm: Cantor Colburn LLP Bowman;
Nicholas
Parent Case Text
DOMESTIC PRIORITY
This application is a continuation of U.S. application Ser. No.
14/560,615, filed on Dec. 4, 2014, the disclosure of which is
incorporated by reference herein in its entirety.
Claims
What is claimed is:
1. A method for iteratively deploying a workload pattern comprising
a plurality of pieces, by a processor, the method comprising:
determining, by the processor, a current set of requirements for at
least one piece of the workload pattern, the workload pattern being
initiated by a user in a designer; generating, by the processor, a
stability metric for each item in the current set of requirements
of the at least one piece of the workload pattern, the stability
metric evaluating a plurality of conditions including at least one
condition selected from a group consisting of a tier dependency
level of the pieces of the workload pattern and a time since last
modification of the workload pattern by the user, the stability
metric comprising a quantitative value indicating a stability of
the at least one piece of the workload pattern with respect to an
ideal time to deploy the at least one piece of the workload
pattern; comparing, by the processor, the stability metric to an
acceptance threshold; calculating, by the processor, an estimated
time to deploy the at least one piece of the workload pattern when
the comparing of the stability metric to the acceptance threshold
indicates that a stability of the at least one piece of the
workload pattern is greater than or equal to the acceptance
threshold; and performing a deployment operation of the at least
one piece of the workload pattern based on the calculated estimated
time to deploy.
2. The method of claim 1, wherein the determining of the current
set of requirements is in response to a save operation or an
asynchronous time interval.
3. The method of claim 1, further comprising: performing a
background deployment operation on the at least one piece of the
workload pattern at a conclusion of the estimated time to deploy,
the background deployment operation configured to deploy the at
least one piece of the workload pattern into an operation
environment.
4. The method of claim 1, wherein the stability metric is based on
at least one of a tier dependency level or a time since the last
modification.
5. The method of claim 1, further comprising: detecting an
extension to the workload pattern; and adjusting the estimated time
to deploy to incorporate any additional provisioning time of the
extension.
6. The method of claim 1, further comprising: presenting, via the
designer, an indication of the estimated time to deploy.
7. The method of claim 1, wherein the stability metric is one of a
plurality of tier stability metrics, wherein the at least one piece
of the workload pattern is included in a plurality of workload
pattern components, each of the plurality of tier stability metrics
corresponds to an item in the current set of requirements and is
utilized to optimize a churn and prioritize a deployment order for
the plurality of workload pattern components.
8. The method of claim 5, wherein when the extension is an addition
of a new virtual machine independent from current virtual machines
in the workload pattern, then a provisioning time of the workload
pattern increases if a provisioning time of the additional virtual
machine is maximum across the new and current virtual machines or
the provisioning time of the workload pattern remains if the
provisioning time of new virtual machine is less than a longest
provisioning time of one of the current virtual machines.
Description
BACKGROUND
The present disclosure relates generally to a concurrent workload
deployment to synchronize activity in design palette, and more
specifically, to a management system configured to partially deploy
into an operation environment pieces of an application workload
concurrent to a designing of the application workload topology in
an editor.
In general, there is a need in cloud environments to provision
virtual machines and application workloads as fast as possible.
Yet, while the provisioning of virtual machines and application
workloads may be optimized via containers, thin-provisioning, and
multi-tenant technologies, the provisioning of thick-provision
virtual machines presently take longer to deploy.
SUMMARY
Embodiments include a method, system, and computer program product
for iteratively deploying a workload pattern that comprises
determining a current set of requirements for at least one piece of
the workload pattern, the workload pattern being initiated in a
designer; generating a stability metric for at least one of the
current set of requirements; comparing the stability metric to an
acceptance threshold; and
calculating an estimated time to deploy the at least one piece of
the workload pattern based on the comparing of the stability metric
to the acceptance threshold.
Additional features and advantages are realized through the
techniques of the present disclosure. Other embodiments and aspects
of the disclosure are described in detail herein. For a better
understanding of the disclosure with the advantages and the
features, refer to the description and to the drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
The subject matter which is regarded as the invention is
particularly pointed out and distinctly claimed in the claims at
the conclusion of the specification. The forgoing and other
features, and advantages of the invention are apparent from the
following detailed description taken in conjunction with the
accompanying drawings in which:
FIG. 1 illustrates a process flow in accordance with an
embodiment;
FIG. 2 illustrates a process flow in accordance with an
embodiment;
FIG. 3 illustrates a process flow in accordance with an
embodiment;
FIG. 4 depicts a cloud computing node according to an embodiment of
the present invention;
FIG. 5 depicts a cloud computing environment according to an
embodiment of the present invention; and
FIG. 6 depicts abstraction model layers according to an embodiment
of the present invention.
DETAILED DESCRIPTION
Embodiments described herein relate to a management system (e.g.,
implemented via a system, a method, and/or computer program
product) configured to partially deploy into an operation
environment pieces of an application workload concurrent to a
designing of the application workload topology in an editor. The
management system enables a confidence metric for a stability of
tiers of the application workload (or workload pattern) to
determine an ideal time to deploy pieces/components or provision
portions of that workload pattern, along with providing an
estimated time to availability as changes are made to the workload
pattern. In this way, the management system optimizes a number of
alterations or churns to the operation environment, so that only
components of the workload pattern that are changed and/or more
likely to stay in the operation environment are redeployed, rather
than redeploying transient components of the workload pattern.
Referring now to FIG. 1, a process flow 100 that describes an
optimization by the management system of deploying a workload
pattern into an operation environment according to one embodiment
is illustrated. The process flow 100 begins at block 105, where the
workload pattern in an editor or designer is initiated.
For example, a workload pattern can be created and/or edited (by a
user) in the designer that is at least part of the management
system, which further operates in alongside or within the operation
environment (e.g., a cloud environment as further described below
with respect to FIG. 4, FIG. 5, and FIG. 6). The operation
environments include configurable aspect, such as components,
virtual machines, virtual images, applications, middleware,
sub-routines, and the like. A workload pattern (or application
workload) is architectural blueprint and scheme that details a
design, build, and/or management these aspects. In turn, the
designer of the management system is a pattern interface that
allows users, through a visual design palette, to design and define
topologies of virtual images, middleware, application roles, etc.
within a workload pattern and then deploy components of that
workload pattern or the workload pattern itself.
Once the workload pattern is initiated, the management system
determines, at block 110, whether the workload pattern is in a
condition for deployment. That is, to reduce the number of churns,
the management system determines a stability of a particular
component of the workload pattern and/or the workload pattern
itself. Then, based on its stability, the management system
determines whether that particular component or the entire workload
pattern itself is in condition for deployment in the operation
environment. The determination of block 110 of the process flow 100
will now be described with respect to FIG. 2.
FIG. 2 illustrates a process flow 200, where at block 205 the
management system determines a current set of requirements for the
workload. This determination can be in response to, for example, a
save operation processed by the management system and/or an
asynchronous time interval. The current set of requirements can
include but are not limited to assets of base operating system
images required for the workload pattern (e.g., a common version of
an operating system is being used in the workload pattern by a
plurality of components); resources assigned to base operating
system instances; connectivity relationships between base operating
system instances; operating system configuration parameters;
operating system software dependencies; middleware requirements;
middleware relationships and connections (e.g., datasource
connections for databases, etc.); user application binaries; and
user application configurations.
At block 210, the management system generates stability metrics for
the current set of requirements. That is, the management system
generates a tier stability metric for each item in the current set
of requirements to optimize a churn and prioritize a deployment
order for the components of the workload pattern (e.g., the stable
components with the higher tier stability metric can be deployed
before those with a lower tier stability metric). The tier
stability metric can be based on tier dependency level; time since
the last modification (e.g., number of iterations observed on the
same component); focus on a specific component in the workload
pattern that is currently being modified; typical and historical
flows for modifications of the workload pattern (e.g. the way users
typically start modifications of the workload pattern by starting
first with the base operating system image, moving to script
packages and add-ons, etc.); time required to execute modifications
to the tier; etc. In addition, at block 210, the management system
can apply inputs to an expression that produces a quantitative
value from 0 to 1 for each tier stability metric, where 1 is a high
stability and 0 is low stability.
For example, with respect to tier dependency level, the management
system can monitor a dependency tree of a stack of the workload
pattern, determine how many components of the stack are utilized by
particular component, and issue a score corresponding to that
utilization for the particular component. Therefore, if a component
of the workload pattern is a common dependent of many components of
the stack, that component will receive a higher score for stability
than a component of the workload pattern that is not a common
dependent (e.g., modifications to an operating system require more
confidence than modification to user application binaries).
Further, with respect to time since the last modification, the
management system can monitor a time since a component of the
workload pattern was changed or loaded into the workload pattern.
In this way, where a component with a longer the life in the
workload pattern would receive a higher score for stability than a
component with a shorter life. For example, if an application was
loaded onto the workload pattern and its lifespan without a change
is three minutes, then that application will have a higher
stability than an application that has a lifespan of three seconds
(e.g., its tier stability metric would be closer to 1 than the
application with the three second lifespan).
At block 215, the management system compares the current set of
requirements to a previous set of requirements. The comparison of
block 215 of the process flow 200 will now be described with
respect to FIG. 3.
FIG. 3 illustrates a process flow 300, where at block 305 the
management system determines differences between the current set of
requirements to a previous set of requirements. For example, the
management system can determine what differences exist with respect
to the last time the requirements were calculated (e.g., any delta
between a configurations) by iterating previous requirements;
discarding requirements that have not changed; identifying old
requirements (e.g., requirement that are no longer present in new
set); and/or identifying new requirements (e.g., determine whether
a requirement was present in old set).
At block 310, the management system generates a list of ongoing
components that are no longer required based on old requirements.
For instance, the management system can generate a list of ongoing
applications that are no longer required (old requirements) in
accordance with the determination of differences between the
current and the previous requirements.
At block 315, the management system generates a set of new
operations that must be met by the workload pattern. In an
embodiment, the management system generates a set of new operations
based on the tier stability metric generated in the process flow
200 and compared to acceptance threshold. For example, if stability
is greater than or equal to an acceptance threshold of N (e.g.,
where N is equal to 0.75), the operation is considered stable
enough to begin provisioning. Further, in the embodiment, the
management system adds tasks for each requirement and/or adds tasks
to reverse old requirements that are no longer valid, as determined
at block 310.
Returning to FIG. 2, the process flow 200 continues to block 220,
where the management system adjusts the ongoing provisioning
activity, such as by canceling operations in-flight that are no
longer required and/or executing a set of delta operations.
Returning to FIG. 1, at block 115, the management system displays
an estimated time to availability for background deployment
operation of the workload pattern. In an embodiment, designer of
the management system is presented as an interface on a display,
where the interface further presents an estimated time to
availability for the background deployment operation. The estimated
time to availability may be presented as an icon, a countdown
timer, a logo, a progress bar and/or a combination of thereof. The
estimated time to availability can be based on aggregated estimated
time for items and/or components to complete, and can dynamically
change to reflect modifications to items and/or components.
At block 120, the management system performs the background
deployment operation of the workload pattern. For example, if the
management system receives an indication (e.g., a user input) to
deploy a completed workload pattern, the management system can wait
for ongoing provisioning operations to complete (or ideally they
may already be complete); migrate the existing pattern to intended
location; and apply specified instance configuration values to the
existing instance. Specified instance configuration values include
but are not limited to network information (e.g., IP address, VLAN,
etc.), authentication data (e.g., username, password, tokens,
etc.), and resource modifications (e.g., changes to disks,
processors, memory, etc.).
At block 125, the management system generates a reference to the
workload pattern. The reference identifies the workload
pattern.
At block 130, the management system provides estimations based on
extending the workload pattern. That is, when the existing pattern
is extended (or contracted), the management system provides an
estimation of how the current deployment time will be affected. For
example, if an extension is an addition of a virtual machine
independent from the rest of the virtual machines in the workload
pattern, then the provisioning time will increase if the additional
virtual machine provisioning time is maximum across all virtual
machines. Further, if an extension is an addition of a virtual
machine independent from the rest of the virtual machines in the
workload pattern, then the provisioning time will remain nearly the
same if new virtual machine provisioning time is less than the
longest provisioning of one of those existing virtual machines.
Furthermore, if an extra script package is added to a virtual
machine, a run-time of script is taken into consideration.
The present invention may be a system (e.g., implemented on a cloud
computing environment), a method, and/or a computer program
product. Further, it is understood in advance that although this
disclosure includes a detailed description on cloud computing,
implementation of the teachings recited herein are not limited to a
cloud computing environment. Rather, embodiments of the present
invention are capable of being implemented in conjunction with any
other type of computing environment now known or later
developed.
The computer program product may include a computer readable
storage medium (or media) having computer readable program
instructions thereon for causing a processor to carry out aspects
and/or embodiments of the present invention. The computer readable
storage medium can be a tangible device that can retain and store
instructions for use by an instruction execution device.
The computer readable storage medium may be, for example, but is
not limited to, an electronic storage device, a magnetic storage
device, an optical storage device, an electromagnetic storage
device, a semiconductor storage device, or any suitable combination
of the foregoing. A non-exhaustive list of more specific examples
of the computer readable storage medium includes the following: a
portable computer diskette, a hard disk, a random access memory
(RAM), a read-only memory (ROM), an erasable programmable read-only
memory (EPROM or Flash memory), a static random access memory
(SRAM), a portable compact disc read-only memory (CD-ROM), a
digital versatile disk (DVD), a memory stick, a floppy disk, a
mechanically encoded device such as punch-cards or raised
structures in a groove having instructions recorded thereon, and
any suitable combination of the foregoing. A computer readable
storage medium, as used herein, is not to be construed as being
transitory signals per se, such as radio waves or other freely
propagating electromagnetic waves, electromagnetic waves
propagating through a waveguide or other transmission media (e.g.,
light pulses passing through a fiber-optic cable), or electrical
signals transmitted through a wire.
Computer readable program instructions described herein can be
downloaded to respective computing/processing devices from a
computer readable storage medium or to an external computer or
external storage device via a network, for example, the Internet, a
local area network, a wide area network and/or a wireless network.
The network may comprise copper transmission cables, optical
transmission fibers, wireless transmission, routers, firewalls,
switches, gateway computers and/or edge servers. A network adapter
card or network interface in each computing/processing device
receives computer readable program instructions from the network
and forwards the computer readable program instructions for storage
in a computer readable storage medium within the respective
computing/processing device.
Computer readable program instructions for carrying out operations
of the present invention may be assembler instructions,
instruction-set-architecture (ISA) instructions, machine
instructions, machine dependent instructions, microcode, firmware
instructions, state-setting data, or either source code or object
code written in any combination of one or more programming
languages, including an object oriented programming language such
as Smalltalk, C++ or the like, and conventional procedural
programming languages, such as the "C" programming language or
similar programming languages. The computer readable program
instructions may execute entirely on the user's computer, partly on
the user's computer, as a stand-alone software package, partly on
the user's computer and partly on a remote computer or entirely on
the remote computer or server. In the latter scenario, the remote
computer may be connected to the user's computer through any type
of network, including a local area network (LAN) or a wide area
network (WAN), or the connection may be made to an external
computer (for example, through the Internet using an Internet
Service Provider). In some embodiments, electronic circuitry
including, for example, programmable logic circuitry,
field-programmable gate arrays (FPGA), or programmable logic arrays
(PLA) may execute the computer readable program instructions by
utilizing state information of the computer readable program
instructions to personalize the electronic circuitry, in order to
perform aspects of the present invention.
Aspects of the present invention are described herein with
reference to flowchart illustrations and/or block diagrams of
methods, apparatus (systems), and computer program products
according to embodiments of the invention. It will be understood
that each block of the flowchart illustrations and/or block
diagrams, and combinations of blocks in the flowchart illustrations
and/or block diagrams, can be implemented by computer readable
program instructions.
These computer readable program instructions may be provided to a
processor of a general purpose computer, special purpose computer,
or other programmable data processing apparatus to produce a
machine, such that the instructions, which execute via the
processor of the computer or other programmable data processing
apparatus, create means for implementing the functions/acts
specified in the flowchart and/or block diagram block or blocks.
These computer readable program instructions may also be stored in
a computer readable storage medium that can direct a computer, a
programmable data processing apparatus, and/or other devices to
function in a particular manner, such that the computer readable
storage medium having instructions stored therein comprises an
article of manufacture including instructions which implement
aspects of the function/act specified in the flowchart and/or block
diagram block or blocks.
The computer readable program instructions may also be loaded onto
a computer, other programmable data processing apparatus, or other
device to cause a series of operational steps to be performed on
the computer, other programmable apparatus or other device to
produce a computer implemented process, such that the instructions
which execute on the computer, other programmable apparatus, or
other device implement the functions/acts specified in the
flowchart and/or block diagram block or blocks.
The flowchart and block diagrams in the Figures illustrate the
architecture, functionality, and operation of possible
implementations of systems, methods, and computer program products
according to various embodiments of the present invention. In this
regard, each block in the flowchart or block diagrams may represent
a module, segment, or portion of instructions, which comprises one
or more executable instructions for implementing the specified
logical function(s). In some alternative implementations, the
functions noted in the block may occur out of the order noted in
the figures. For example, two blocks shown in succession may, in
fact, be executed substantially concurrently, or the blocks may
sometimes be executed in the reverse order, depending upon the
functionality involved. It will also be noted that each block of
the block diagrams and/or flowchart illustration, and combinations
of blocks in the block diagrams and/or flowchart illustration, can
be implemented by special purpose hardware-based systems that
perform the specified functions or acts or carry out combinations
of special purpose hardware and computer instructions.
With respect to implementing aspect and/or embodiments of the
present invention on cloud computing environment, cloud computing
in general is a model of service delivery for enabling convenient,
on-demand network access to a shared pool of configurable computing
resources (e.g. networks, network bandwidth, servers, processing,
memory, storage, applications, virtual machines, and services) that
can be rapidly provisioned and released with minimal management
effort or interaction with a provider of the service. This cloud
model may include at least five characteristics, at least three
service models, and at least four deployment models.
Characteristics can be on-demand self-service; broad network
access; resource pooling; rapid elasticity; and measured
service.
On-demand self-service: a cloud consumer can unilaterally provision
computing capabilities, such as server time and network storage, as
needed automatically without requiring human interaction with the
service's provider.
Broad network access: capabilities are available over a network and
accessed through standard mechanisms that promote use by
heterogeneous thin or thick client platforms (e.g., mobile phones,
laptops, and PDAs).
Resource pooling: the provider's computing resources are pooled to
serve multiple consumers using a multi-tenant model, with different
physical and virtual resources dynamically assigned and reassigned
according to demand. There is a sense of location independence in
that the consumer generally has no control or knowledge over the
exact location of the provided resources but may be able to specify
location at a higher level of abstraction (e.g., country, state, or
datacenter).
Rapid elasticity: capabilities can be rapidly and elastically
provisioned, in some cases automatically, to quickly scale out and
rapidly released to quickly scale in. To the consumer, the
capabilities available for provisioning often appear to be
unlimited and can be purchased in any quantity at any time.
Measured service: cloud systems automatically control and optimize
resource use by leveraging a metering capability at some level of
abstraction appropriate to the type of service (e.g., storage,
processing, bandwidth, and active user accounts). Resource usage
can be monitored, controlled, and reported providing transparency
for both the provider and consumer of the utilized service.
Three service models can include Software as a Service (SaaS);
Platform as a Service (PaaS); and Infrastructure as a Service
(IaaS).
SaaS: the capability provided to the consumer is to use the
provider's applications running on a cloud infrastructure. The
applications are accessible from various client devices through a
thin client interface such as a web browser (e.g., web-based
email). The consumer does not manage or control the underlying
cloud infrastructure including network, servers, operating systems,
storage, or even individual application capabilities, with the
possible exception of limited user-specific application
configuration settings.
PaaS: the capability provided to the consumer is to deploy onto the
cloud infrastructure consumer-created or acquired applications
created using programming languages and tools supported by the
provider. The consumer does not manage or control the underlying
cloud infrastructure including networks, servers, operating
systems, or storage, but has control over the deployed applications
and possibly application hosting environment configurations.
IaaS: the capability provided to the consumer is to provision
processing, storage, networks, and other fundamental computing
resources where the consumer is able to deploy and run arbitrary
software, which can include operating systems and applications. The
consumer does not manage or control the underlying cloud
infrastructure but has control over operating systems, storage,
deployed applications, and possibly limited control of select
networking components (e.g., host firewalls).
The deployment models can include private cloud; community cloud,
public cloud; and hybrid cloud.
Private cloud: the cloud infrastructure is operated solely for an
organization. It may be managed by the organization or a third
party and may exist on-premises or off-premises.
Community cloud: the cloud infrastructure is shared by several
organizations and supports a specific community that has shared
concerns (e.g., mission, security requirements, policy, and
compliance considerations). It may be managed by the organizations
or a third party and may exist on-premises or off-premises.
Public cloud: the cloud infrastructure is made available to the
general public or a large industry group and is owned by an
organization selling cloud services.
Hybrid cloud: the cloud infrastructure is a composition of two or
more clouds (private, community, or public) that remain unique
entities but are bound together by standardized or proprietary
technology that enables data and application portability (e.g.,
cloud bursting for load balancing between clouds).
A cloud computing environment is service oriented with a focus on
statelessness, low coupling, modularity, and semantic
interoperability. At the heart of cloud computing is an
infrastructure comprising a network of interconnected nodes.
Referring now to FIG. 4, a schematic of an example of a cloud
computing node is shown. A cloud computing node 410 is only one
example of a suitable cloud computing node and is not intended to
suggest any limitation as to the scope of use or functionality of
embodiments of the invention described herein. Regardless, the
cloud computing node 410 is capable of being implemented and/or
performing any of the functionality set forth hereinabove.
In the cloud computing node 410 there is a computer system/server
412, which is operational with numerous other general purpose or
special purpose computing system environments or configurations.
Examples of well-known computing systems, environments, and/or
configurations that may be suitable for use with the computer
system/server 412 include, but are not limited to, personal
computer systems, server computer systems, thin clients, thick
clients, handheld or laptop devices, multiprocessor systems,
microprocessor-based systems, set top boxes, programmable consumer
electronics, network PCs, minicomputer systems, mainframe computer
systems, and distributed cloud computing environments that include
any of the above systems or devices, and the like.
The computer system/server 412 may be described in the general
context of computer system executable instructions, such as program
modules, being executed by a computer system. Generally, program
modules may include routines, programs, objects, components, logic,
data structures, and so on that perform particular tasks or
implement particular abstract data types. The computer
system/server 412 may be practiced in distributed cloud computing
environments where tasks are performed by remote processing devices
that are linked through a communications network. In a distributed
cloud computing environment, program modules may be located in both
local and remote computer system storage media including memory
storage devices.
As shown in FIG. 4, the computer system/server 412 in the cloud
computing node 410 is shown in the form of a general-purpose
computing device. The components of the computer system/server 412
may include, but are not limited to, one or more processors or
processing units (e.g., processor 414), a system memory 416, and a
bus 418 that couples various system components including the system
memory 416 to the processor 414.
The bus 418 represents one or more of any of several types of bus
structures, including a memory bus or memory controller, a
peripheral bus, an accelerated graphics port, and a processor or
local bus using any of a variety of bus architectures. By way of
example, and not limitation, such architectures include Industry
Standard Architecture (ISA) bus, Micro Channel Architecture (MCA)
bus, Enhanced ISA (EISA) bus, Video Electronics Standards
Association (VESA) local bus, and Peripheral Component Interconnect
(PCI) bus.
The computer system/server 412 typically includes a variety of
computer system readable media. Such media may be any available
media that is accessible by the computer system/server 412, and it
includes both volatile and non-volatile media, removable and
non-removable media.
The system memory 416 can include computer system readable media in
the form of volatile memory, such as a random access memory (RAM)
420 and/or a cache memory 422. The computer system/server 412 may
further include other removable/non-removable,
volatile/non-volatile computer system storage media. By way of
example only, storage system 424 can be provided for reading from
and writing to a non-removable, non-volatile magnetic media (not
shown and typically called a "hard drive"). Although not shown, a
magnetic disk drive for reading from and writing to a removable,
non-volatile magnetic disk (e.g., a "floppy disk"), and an optical
disk drive for reading from or writing to a removable, non-volatile
optical disk such as a CD-ROM, DVD-ROM or other optical media can
be provided. In such instances, each can be connected to the bus
418 by one or more data media interfaces. As will be further
depicted and described below, the system memory 416 may include at
least one program product having a set (e.g., at least one) of
program modules that are configured to carry out the functions of
embodiments of the invention.
For example, a program/utility 426, having a set (at least one) of
program modules (e.g., a program module 428), may be stored in the
system memory 416 by way of example, and not limitation, as well as
an operating system, one or more application programs, other
program modules, and program data. Each of the operating system,
one or more application programs, other program modules, and
program data or some combination thereof, may include an
implementation of a networking environment. The program modules 426
generally carry out the functions and/or methodologies of
embodiments of the invention as described herein.
The computer system/server 412 may also communicate (e.g., via
Input/Output (I/O) interfaces, such as I/O interface 430) with one
or more external devices, such as a keyboard 440, a pointing
device, a display 442, etc.; one or more devices that enable a user
to interact with the computer system/server 412; and/or any devices
(e.g., network card, modem, etc.) that enable the computer
system/server 412 to communicate with one or more other computing
devices. Still yet, the computer system/server 412 can communicate
with one or more networks such as a local area network (LAN), a
general wide area network (WAN), and/or a public network (e.g., the
Internet) via a network adapter 444. As depicted, the network
adapter 444 communicates with the other components of the computer
system/server 412 via the bus 418. It should be understood that
although not shown, other hardware and/or software components could
be used in conjunction with the computer system/server 412.
Examples, include, but are not limited to: microcode, device
drivers, redundant processing units, external disk drive arrays,
RAID systems, tape drives, and data archival storage systems,
etc.
Referring now to FIG. 5, illustrative cloud computing environment
550 is depicted. As shown, the cloud computing environment 550
comprises one or more cloud computing nodes 410 with which local
computing devices used by cloud consumers, such as, for example, a
personal digital assistant (PDA) or cellular telephone 554A, a
desktop computer 554B, a laptop computer 554C, and/or an automobile
computer system 554N may communicate. The cloud computing nodes 410
may communicate with one another. They may be grouped (not shown)
physically or virtually, in one or more networks, such as Private,
Community, Public, or Hybrid clouds as described hereinabove, or a
combination thereof. This allows cloud computing environment 550 to
offer infrastructure, platforms and/or software as services for
which a cloud consumer does not need to maintain resources on a
local computing device. It is understood that the types of
computing devices 554A-N shown in FIG. 5 are intended to be
illustrative only and that the computing nodes 410 and cloud
computing environment 550 can communicate with any type of
computerized device over any type of network and/or network
addressable connection (e.g., using a web browser).
Referring now to FIG. 6, a set of functional abstraction layers
provided by cloud computing environment 550 (FIG. 5) is shown. It
should be understood in advance that the components, layers, and
functions shown in FIG. 6 are intended to be illustrative only and
embodiments of the invention are not limited thereto. As depicted,
the following layers and corresponding functions are provided:
A hardware and software layer 660 includes hardware and software
components. Examples of hardware components include: mainframes;
RISC (Reduced Instruction Set Computer) architecture based servers;
storage devices; networks and networking components. In some
embodiments, software components include network application server
software.
A virtualization layer 662 provides an abstraction layer from which
the following examples of virtual entities may be provided: virtual
servers; virtual storage; virtual networks, including virtual
private networks; virtual applications and operating systems; and
virtual clients.
In one example, a management layer 664 may provide the functions
described below. Resource provisioning provides dynamic procurement
of computing resources and other resources that are utilized to
perform tasks within the cloud computing environment. Metering and
Pricing provide cost tracking as resources are utilized within the
cloud computing environment, and billing or invoicing for
consumption of these resources. In one example, these resources may
comprise application software licenses. Security provides identity
verification for cloud consumers and tasks, as well as protection
for data and other resources. User portal provides access to the
cloud computing environment for consumers and system
administrators.
Service level management provides cloud computing resource
allocation and management such that required service levels are
met. Service Level Agreement (SLA) planning and fulfillment
provides pre-arrangement for, and procurement of, cloud computing
resources for which a future requirement is anticipated in
accordance with an SLA.
A workloads layer 666 provides examples of functionality for which
the cloud computing environment may be utilized. Examples of
workloads and functions which may be provided from this layer
include: mapping and navigation; software development and lifecycle
management; virtual classroom education delivery; data analytics
processing; transaction processing; and mobile desktop.
In view of the above, the management system improves deployment use
cases for creating new workload patterns or making changes to
existing patterns in that as interactions with a pattern in a
designer of the management system occur, deployment of the pattern
are executed in parallel based on a current state of the pattern.
Further, adjustments to any deployed instance of the pattern can
occur as continued changes are made in the designer, while visual
representation indicate the status of the deployed instances and
the pattern in the designer. Thus, the technical effects and
benefits of the management system include concurrent provisioning
of a workload pattern during design; providing confidence metrics
quantifying a stability of a workload tier or component of a
workload pattern during design; providing estimated times to
availability of deployed instances as modifications are made to a
workload pattern during design; providing estimations as to how
provisioning time will be changed without actually putting changes
in place when existing workload patterns are extended; and
displaying potential run time errors workload pattern during
design. Technical effects and benefits of the management system
also include optimizing provisioning time of complex application
workloads; reducing time to value; improving problem determination
and speed; improve user first impression of cloud management
experience; and increasing effectiveness of management system for
development and operations paradigms.
The terminology used herein is for the purpose of describing
particular embodiments only and is not intended to be limiting of
the invention. As used herein, the singular forms "a", "an" and
"the" are intended to include the plural forms as well, unless the
context clearly indicates otherwise. It will be further understood
that the terms "comprises" and/or "comprising," when used in this
specification, specify the presence of stated features, integers,
steps, operations, elements, and/or components, but do not preclude
the presence or addition of one more other features, integers,
steps, operations, element components, and/or groups thereof.
The corresponding structures, materials, acts, and equivalents of
all means or step plus function elements in the claims below are
intended to include any structure, material, or act for performing
the function in combination with other claimed elements as
specifically claimed. The description of the present invention has
been presented for purposes of illustration and description, but is
not intended to be exhaustive or limited to the invention in the
form disclosed. Many modifications and variations will be apparent
to those of ordinary skill in the art without departing from the
scope and spirit of the invention. The embodiment was chosen and
described in order to best explain the principles of the invention
and the practical application, and to enable others of ordinary
skill in the art to understand the invention for various
embodiments with various modifications as are suited to the
particular use contemplated.
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